IARPA is specifically interested in LLKM methods that help users discover the causes of their successes and failures. Perhaps more importantly, IARPA wants to mitigate user bias when they assess the lessons they should learn. This includes judgment and memory biases, such as fundamental attribution errors and hindsight memory bias, as well as better counterfactual reasoning to understand how there might have been different outcomes had they made different decisions. IARPA also seeks metrics to assess these factors.